Detection of outliers in the response and explanatory variables of the simple circular regression model

Citation

Mahmood, Ehab A. and Rana, Md. Sohel and Hussin, Abdul Ghapor and Midi, Habshah (2016) Detection of outliers in the response and explanatory variables of the simple circular regression model. In: 2nd International Conference on Mathematical Sciences and Statistics (ICMSS2016), 26-28 Jan. 2016, Kuala Lumpur, Malaysia. (pp. 1-7).

Abstract

The circular regression model may contain one or more data points which appear to be peculiar or inconsistent with the main part of the model. This may be occur due to recording errors, sudden short events, sampling under abnormal conditions etc. The existence of these data points “outliers” in the data set cause lot of problems in the research results and the conclusions. Therefore, we should identify them before applying statistical analysis. In this article, we aim to propose a statistic to identify outliers in the both of the response and explanatory variables of the simple circular regression model. Our proposed statistic is robust circular distance RCDxy and it is justified by the three robust measurements such as proportion of detection outliers, masking and swamping rates.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Science Institute for Mathematical Research
DOI Number:	https://doi.org/10.1063/1.4952561
Publisher:	AIP Publishing
Keywords:	Circular data; Circular regression; Outlier; Masking and swamping
Depositing User:	Nabilah Mustapa
Date Deposited:	08 Sep 2017 09:41
Last Modified:	10 Jan 2018 05:34
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1063/1.4952561
URI:	http://psasir.upm.edu.my/id/eprint/57181
Statistic Details:	View Download Statistic

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